Havea Pharma: assessing and rebalancing its sales force workload plan

“What mattered most to me when I decided to work with Datakiss was being able to assess whether my reps, given their working time, could deliver the workload plan we were asking of them: being in the right place at the right time.”
David Covin, Sales Director, Havea Pharma BU

Havea Pharma at a glance

Historically based in Vendée, the Havea group is a natural health specialist and the European leader in food supplements. Its well-known brands include Aragan, Densmore and Biocyte internationally, Dermovitamina and Be-Life in Germany, and Biolane and Calmosine in pharmacies and consumer goods.

This testimonial comes from David Covin, Sales Director of the Havea Pharma BU. He works closely with marketing, sales administration, his four regional directors and the key accounts team to define the workload plan.

stat: 35 | pharmaceutical sales reps

stat: 4 | regional directors

stat: N°1 | in food supplements in Europe

The challenge: a sustainable workload plan, territory by territory

To cover the whole country, Havea Pharma relies on 35 reps spread across four regions. David Covin’s question was simple, yet fundamental: is each rep truly able, within their working time, to deliver the workload plan asked of them? Three issues were at stake:

• Validate the sizing of the sales force. Was the headcount sufficient given the needs and the potential targets set?
• Objectively measure over- and under-pressure. Some territories were under excessive visit pressure, others under too little, with no factual view to establish it.
• Be in the right place at the right time. Ensure every customer is seen at the right frequency, depending on the territory and the number of customers.

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“Being in the right place at the right time, as I often say: depending on their territory, the number of customers they had and their ability to see, at the right frequency, all the potential we had identified.”
David Covin, Sales Director, Havea Pharma BU

The Datakiss solution: a factual, collaborative approach

To address these issues, Havea Pharma relies on Datakiss Territory Planning. The project starts from templates completed together with Datakiss, which the tool cross-analyzes to assess the feasibility of the workload plan, territory by territory.

1. Collection of rep data and customer data by UGA (geographic analysis unit)
   • The templates include concrete field parameters: where each rep lives, their geographic territory, all the UGAs covering their area, the customers in the territory and the priority prospects to include in the workload plan.
2. Modeling in Datakiss Territory Planning
3. Assessment of each rep’s workload plan
4. A rebalanced territory design with a controlled workload

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“What I particularly appreciated was how factual the rollout of this project was. We started from templates completed together with Datakiss.”
David Covin, Sales Director, Havea Pharma BU

Project benefits

David Covin highlights three main benefits:

• Validating the right sizing of the sales force: checking that the headcount matches the needs.
• Identifying, territory by territory: the areas under too much or too little visit pressure.
• Rebalancing the territory design: reallocating UGAs to under-pressured reps and adding priority prospects, for a workload that is sufficient but never excessive, which is essential to meeting the visit frequency customers expect.

The key to success

For David Covin, the strength of the project lies in its approach: factual, co-built and grounded in each rep’s real field data.

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“By reallocating UGAs to under-pressured reps, and even adding priority prospects, we made sure every territory had enough work, and above all not too much activity, which would not meet customer expectations.”
David Covin, Sales Director, Havea Pharma BU

Overview: a rebalanced network

This analysis covers the network’s 35 territories. Between the initial diagnosis and the territory design recommended with the regional directors, with the same headcount and selling time, the network becomes much more balanced: average workload falls back below target and overloaded territories drop by 30%.

stat-bis: 104 → 98 % | average workload, below target

stat-bis: −30 % | overloaded territories

stat-bis: 123 → 112 % | peak workload capped

Key changes

• Average workload: back below the 100% target (from 104% to 98%), restoring the right sizing.
• Overloads: −30% territories above target (from 23 to 16).
• Extreme peaks resolved: the most heavily loaded territory drops from 123% to 112%, with no unmanageable cases left.
• Greater fairness: gaps between territories narrow, with most of the network now within a healthy workload band.
• Coverage preserved: face-to-face time and driving time remain stable, so the rebalancing does not come at the expense of field presence.
• National performance: up one notch, from C+ to B-.

In summary

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“Making sure each territory has enough work, and above all not too much activity: being able to see all our customers the way we want, at the right frequency and at the right time.”
David Covin, Sales Director, Havea Pharma BU